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zo& Gase Report [draft] Business Problem Our company have market a hybrid product integrating a Personal DigitalAssistant (PDA) with a "smad" cellular phone, ConneCtor. ConneCtor directly transmits and receives both data and voice. lt is lightweight but heavier than a cell phone whose shape it emulates. lt comes with a backlit grayscale LCD screen of moderate resolution. lts operating system is the PalmOS, which is common in PDAs. Thus, ConneCtor allows the user, among other things, to access the standard tools of Personal lnformation Management (PlM) and also pefforms standard cell phone functions. The key features of ConneCtor includes (1) lnstant cofimunication for voice and data, (2) Cell phone, pager, fax and Email, and instant messaging, (3)PlM functions, (4) Digitalvoice recorder, (5) Enabled voice commands, (6) PalmOS application base. We want to find a specific market segmentation which is perfectly match our product. Thus, Our Netlink's management hired a market research firm, Happy Valley Consultants (HVC), to collect information about the needs of ConneCtor's potential customers. We identify two sets of key targeting criteria: (1) Producttarget market fit, in terms of Conglomerate's technical strengths, market needs and the ability of the current (or future) ConneCtors to meet those needs, (2) Segment size and growth expectations, including both first purchases and upgradeireplacement buys. We exploit the collected data for further analysis in the subsequent section. Analysis C>L*Jr'L4-=('1v"'L 2b J*' L-J,.y ) u kj', U(Z-A ;i^ ifib)f, we9nritris)toanalyzethedata,and1trytoidentifythe weis)toanalyzethedata,.and1trytoidentifyth . /l ;;"';'{L e> ;;;-;L A-O LL-'- (J; market - seoments and address the business oroblem accordinolv / a\ We first rua.PCA with 9 clusters to generate \ dendogram, the data can be clustered due to the distance. More specifically, we can cluster 4 and 9 at distance fcluster 1 and 8 at distance 5nd 6 at distance 0.28, and merge 0.26, cluster 5 and 7 at distance 0.27, merge cluster cluster 2, 5 and 7 at distance 0.34. However, that 1) most distances between data small range but holds many clusters; 2) some are below 0.34 and distance 0.25-0.28 "short clusters have very distance" vb+Cfi don't count for a distinct category, which means the segmentation variables are irdly similar, 3) there are several clusters in 9-cluster solution only got small size which be potentially merged by other group, e.9., Cluster t has 14 respondent, Cluster 2 1.11 .2S .'27 .26 LB Fig.1 Dendogram of, clusters' sizes in 9-Cluster solution 4 CiusterlD Fig.3 Dendogram of 4-Clusters solution Thus, based on these three observations, we consider that both 4-clusters (take distance 0.34) and S-clusters (take distance 0.28) are possible solution, so we compare these two solutions and re-run the Analysis using cluster number as 4 and 5. As shown in Fig. 3, we can see that the distance between 4 clusters are quite significant, the segmentation variables between these 4 cluster are also distinctive (see Fig 4). Also, most cluster has a sufficient amount of respondents, only cluster 3 has 16 respondents which is still more than some clusters in gclusters solution, as shown in Fig 5. ir r',.rr'.:'.:1,, *n..-:::,..1.i . !.t_ .j .,r:i -i.c j-). t".:. iegmeniati on yariabi e I Sverall f,luster nnsvatgr Cluseer 1 Ctuster 2.1; 3"47 Ltss Megssge 4"3:. 5.56 tjse Cell Lise P,M lnf Pa:siye nf Aciiue Aerncie Aaaess 4.*1 4.4t ihare lnf .3.t r,{onhEr 4.7' irnail 4"72 rgon*mi: Vlonthly arice / 5.fl: 3-J = re* A"?e ,/ {o# f,'i y' 4"Bt 28"8 a?a Cla:terp 4 4f j,f,: 5.8i f,4-i ,1 r ,r"a1 3 3.43 5.&4 frteb Mmedia eluster s.6E 4.5 a !q t :9 J.UD : ll t.&t )* / 3.i i S,&{ : T1 !, ir 5.35 4.42 i.59 J.J ] 1f,.r tr.44 :,.{5 _t,:+ 4,1e ).] 5. "ff,: ,:i.J 3-C.d ,i{ * 1.! j Fig.a Segyentation Variables of 4-Clusters solution L ,-. iiJ9rtf. si;*> i Size l'"$ um /CIust*r cblerv*iisni ber trf Prcpctrtirrn OyerafI Cluster 1 16r C1us..............1er? ]I 9.35 *.i1$ Cluster 3 CluEter 4 1D u"t*r1 Fig.5 The individual clusters' sizes in 4-Cluster solution We also test S-clusters case. As shown in Fig. 6, we can see that the distance between 5 clusters are significant. However, the segmentation variables between these 5 cluster are not as much distinctive as what we have in 4-Cluster solution (see Fig. 4 and Fig.7). Furthermore, as shown in Fig' 8, the cluster 2 only has 11 members. Too fine-grained clustering is not suitable to a new product. uorlnlos sJolsnlc-t lo selqetren uotlelueuoes /.611 r)cI nii LE+ JOL 9'F.T ?"4t d"tz o'b7 a"8e iir.llu*t4 v q6rfl p"t rtuouoB.rl vi'T I-L L Y,l , iF'? *'r rB'ts td:'t aqrd La6 Ftj"I rd'q f ElFELlrh f h'* tr'-tr H! l3r'-V i iT'* tr'{ ;r"I :7'.: F9"E re '? f;"r r?'E F*"f qarll l!Errj: 5t'r' ro}luolA t"t Jut a€q! s5*3iva}*ilal I Y5 L 50 t T'I arljilY Jul ,-, y lra'f r8'.1: 4.tu'r -iB"ts *a'7 vt Ai"7 ! lalsnlf ?latrsnl} t ra]5]rD i7'c $0'c 5F'T I l'q tr aArssed +ul j Ja]sn,:! tr rElsnlf l"{ld p5's llaf asn a8essary asg tF't ll€.rEAO lsleAguu ralsfi13 / a HEFEit LE ll€+uarugag 'lalJeul stq] ul slueuJ6€s lcullslp ? oJe eJoL,l] leLll oA 'uotsnlcuoo e sV ']lnsoJ Jeltu.lts fuen e saptnoJd poqleui (f=y) sueeul-y '01 0!j pue^ltluepr 6'6tJ ur paluosaid sV'uoticolas Jno LrtUUoc ol poqleLu sueoLu-y osn eA 'sls{lEue lEolL.icJeJetLl eL{l uo poseq uot}nlos le}snlC-, }celes aM q$noqllv uorinlos srelsnlS-g lo ureroopuec g ci lalsnl:) 0ll 9Z'I TT'T -: 6'r o) fl c)l o: .Size./Cluster 0rrera[l of shseryaii$nE Pr*parti*rr f.iu rn,ber CluEter 1 Cluster2 1sC fi.35 u "{_i Clugter 3 Cluster 4 11 1d .:1 o )l U.I CI"t51 Ltuster: {t.35 Fig.8 The individual clusters' sizes in 4-Cluster solution Segrc entati m yariabl er Ovsrall Cl*ster lnnsvator Clusier ? na 5.56 Jse PIM nf Fassirie nf Active lemrrie Access 4-: 3. ?! ih*re !nf 3.71 !,lonitor 4.75 J, / d 5$i a,a.t -1 i a':. ri f .Ur ! ,- i. t Purchase answer to see full attachment

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